919 citations
- Massachusetts Institute of TechnologyUS27 papers
- Harvard UniversityUS7 papers
- Institute of Cognitive and Brain SciencesUS7 papers
- Chinese Institute for Brain ResearchCN5 papers
- Tsinghua UniversityCN4 papers
- Beijing Academy of Artificial IntelligenceCN3 papers
- Beijing Normal UniversityCN3 papers
- Columbia UniversityUS3 papers
- Harvard–MIT Division of Health Sciences and TechnologyUS3 papers
- IIT@MITUS3 papers
- Italian Institute of TechnologyIT3 papers
- University of California, BerkeleyUS3 papers
6 papers · 1 filter
Knowing what you know in brain segmentation using Bayesian deep neural networks
Patrick McClure, Nao Rho, John A. Lee +7
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was tra…
Sarcasm Analysis using Conversation Context
Debanjan Ghosh, Alexander R. Fabbri, Smaranda Muresan
Computational models for sarcasm detection have often relied on the content of utterances in isolation. However, the speaker's sarcastic intent is not always apparent without addit…
Dynamic self-organized error-correction of grid cells by border cells
Eli Pollock, Niral Desai, Xue-Xin Wei +1
Grid cells in the entorhinal cortex are believed to establish their regular, spatially correlated firing patterns by path integration of the animal's motion. Mechanisms for path in…
JUMPER: Learning When to Make Classification Decisions in Reading
Xianggen Liu, Lili Mou, Haotian Cui +2
In early years, text classification is typically accomplished by feature-based machine learning models; recently, deep neural networks, as a powerful learning machine, make it poss…
Deep-learning Based Modeling of Fault Detachment Stability for Power Grid
Haotian Cui, Xianggen Liu, Yanhao Huang
The project intends to model the stability of power system with a deep learning algorithm to the problem, aiming to delay the removal of the fault. The so-called "fail-delay cut-of…
Slip Detection with Combined Tactile and Visual Information
Jianhua Li, Siyuan Dong, Edward Adelson
Slip detection plays a vital role in robotic manipulation and it has long been a challenging problem in the robotic community. In this paper, we propose a new method based on deep…